Ethics, subjective well-being, and trust as determinants of the adoption of AI-based digital banking chatbots

The accelerated adoption of digital banking and the growing implementation of artificial intelligence (AI)-driven chatbots are reshaping financial services. This study examines the role of ethical perception, subjective well-being, and trust as determinants of the intention to use banking chatbots. Specifically, it aims to test an extended version of the Unified Theory of Acceptance and Use of Technology 2, incorporating ethical and psychological dimensions often overlooked in adoption models. A quantitative, non-experimental, cross-sectional, and causal design was applied with data collected from 274 users of digital banking and chatbots. The analysis was conducted through covariance-based structural equation modelling (CB-SEM), allowing the evaluation of direct and indirect effects among the constructs. Results indicate that ethical perception positively affects subjective well-being and trust, but not directly the intention to use. In contrast, subjective well-being and trust strongly affected intention to use. Furthermore, mediation analysis revealed that ethical perception influences adoption indirectly through well-being and trust. These findings highlight the need for banking institutions to design chatbots that are not only technically efficient, also ethically transparent and emotionally supportive. The study expands UTAUT2 by integrating ethical and psychological variables, providing a more human-centred framework for understanding the adoption of AI in financial services.